Read count after removing mitochondrial reads (final read count)
14,286,262
Note that all these read counts are determined using 'samtools view' - as such,
these are all reads found in the file, whether one end of a pair or a single
end read. In other words, if your file is paired end, then you should divide
these counts by two. Each step follows the previous step; for example, the
duplicate reads were removed after reads were removed for low mapping quality.
This bar chart also shows the filtering process and where the reads were lost
over the process. Note that each step is sequential - as such, there may
have been more mitochondrial reads which were already filtered because of
high duplication or low mapping quality. Note that all these read counts are
determined using 'samtools view' - as such, these are all reads found in
the file, whether one end of a pair or a single end read. In other words,
if your file is paired end, then you should divide these counts by two.
Alignment statistics
Bowtie alignment log
31605408 reads; of these:
31605408 (100.00%) were paired; of these:
2231425 (7.06%) aligned concordantly 0 times
8744837 (27.67%) aligned concordantly exactly 1 time
20629146 (65.27%) aligned concordantly >1 times
----
2231425 pairs aligned concordantly 0 times; of these:
661651 (29.65%) aligned discordantly 1 time
----
1569774 pairs aligned 0 times concordantly or discordantly; of these:
3139548 mates make up the pairs; of these:
1055949 (33.63%) aligned 0 times
108756 (3.46%) aligned exactly 1 time
1974843 (62.90%) aligned >1 times
98.33% overall alignment rate
Samtools flagstat
167967377 + 0 in total (QC-passed reads + QC-failed reads)
104756561 + 0 secondary
0 + 0 supplementary
0 + 0 duplicates
166911428 + 0 mapped (99.37%:-nan%)
63210816 + 0 paired in sequencing
31605408 + 0 read1
31605408 + 0 read2
58747966 + 0 properly paired (92.94%:-nan%)
62032300 + 0 with itself and mate mapped
122567 + 0 singletons (0.19%:-nan%)
425130 + 0 with mate mapped to a different chr
42360 + 0 with mate mapped to a different chr (mapQ>=5)
Note that the flagstat command counts alignments, not reads. please
use the read counts table to get accurate counts of reads at each
stage of the pipeline.
Filtering statistics
Mapping quality > q30 (out of total)
40,033,146
0.633
Duplicates (after filtering)
12,084,394
0.628
Mitochondrial reads (out of total)
46,283,404
0.277
Duplicates that are mitochondrial (out of all dups)
23,149,826
0.958
Final reads (after all filters)
14,286,262
0.226
Mapping quality refers to the quality of the read being aligned to that
particular location in the genome. A standard quality score is > 30.
Duplications are often due to PCR duplication rather than two unique reads
mapping to the same location. High duplication is an indication of poor
libraries. Mitochondrial reads are often high in chromatin accessibility
assays because the mitochondrial genome is very open. A high mitochondrial
fraction is an indication of poor libraries. Based on prior experience, a
final read fraction above 0.70 is a good library.
Library complexity statistics
ENCODE library complexity metrics
Metric
Result
NRF
0.916475 - OK
PBC1
0.985944 - OK
PBC2
78.824171 - OK
The non-redundant fraction (NRF) is the fraction of non-redundant mapped reads
in a dataset; it is the ratio between the number of positions in the genome
that uniquely mapped reads map to and the total number of uniquely mappable
reads. The NRF should be > 0.8. The PBC1 is the ratio of genomic locations
with EXACTLY one read pair over the genomic locations with AT LEAST one read
pair. PBC1 is the primary measure, and the PBC1 should be close to 1.
Provisionally 0-0.5 is severe bottlenecking, 0.5-0.8 is moderate bottlenecking,
0.8-0.9 is mild bottlenecking, and 0.9-1.0 is no bottlenecking. The PBC2 is
the ratio of genomic locations with EXACTLY one read pair over the genomic
locations with EXACTLY two read pairs. The PBC2 should be significantly
greater than 1.
Picard EstimateLibraryComplexity
11,931,741
Yield prediction
Preseq performs a yield prediction by subsampling the reads, calculating the
number of distinct reads, and then extrapolating out to see where the
expected number of distinct reads no longer increases. The confidence interval
gives a gauge as to the validity of the yield predictions.
Fragment length statistics
Metric
Result
Fraction of reads in NFR
0.349165754795 out of range [0.4, inf]
NFR / mono-nuc reads
0.950375316459 out of range [2.5, inf]
Presence of NFR peak
OK
Presence of Mono-Nuc peak
OK
Presence of Di-Nuc peak
OK
Open chromatin assays show distinct fragment length enrichments, as the cut
sites are only in open chromatin and not in nucleosomes. As such, peaks
representing different n-nucleosomal (ex mono-nucleosomal, di-nucleosomal)
fragment lengths will arise. Good libraries will show these peaks in a
fragment length distribution and will show specific peak ratios.
Peak statistics
Metric
Result
Naive overlap peaks
162066 - OK
IDR peaks
76312 - OK
Naive overlap peak file statistics
Min size
73.0
25 percentile
228.0
50 percentile (median)
386.0
75 percentile
640.0
Max size
2267.0
Mean
470.962521442
IDR peak file statistics
Min size
73.0
25 percentile
426.0
50 percentile (median)
621.0
75 percentile
864.0
Max size
2267.0
Mean
665.812703114
For a good ATAC-seq experiment in human, you expect to get 100k-200k peaks
for a specific cell type.
Sequence quality metrics
GC bias
Open chromatin assays are known to have significant GC bias. Please take this
into consideration as necessary.
Read count after removing mitochondrial reads (final read count)
15,061,194
Note that all these read counts are determined using 'samtools view' - as such,
these are all reads found in the file, whether one end of a pair or a single
end read. In other words, if your file is paired end, then you should divide
these counts by two. Each step follows the previous step; for example, the
duplicate reads were removed after reads were removed for low mapping quality.
This bar chart also shows the filtering process and where the reads were lost
over the process. Note that each step is sequential - as such, there may
have been more mitochondrial reads which were already filtered because of
high duplication or low mapping quality. Note that all these read counts are
determined using 'samtools view' - as such, these are all reads found in
the file, whether one end of a pair or a single end read. In other words,
if your file is paired end, then you should divide these counts by two.
Alignment statistics
Bowtie alignment log
39069894 reads; of these:
39069894 (100.00%) were paired; of these:
2769616 (7.09%) aligned concordantly 0 times
9999602 (25.59%) aligned concordantly exactly 1 time
26300676 (67.32%) aligned concordantly >1 times
----
2769616 pairs aligned concordantly 0 times; of these:
716720 (25.88%) aligned discordantly 1 time
----
2052896 pairs aligned 0 times concordantly or discordantly; of these:
4105792 mates make up the pairs; of these:
1552341 (37.81%) aligned 0 times
116305 (2.83%) aligned exactly 1 time
2437146 (59.36%) aligned >1 times
98.01% overall alignment rate
Samtools flagstat
211883832 + 0 in total (QC-passed reads + QC-failed reads)
133744044 + 0 secondary
0 + 0 supplementary
0 + 0 duplicates
210331491 + 0 mapped (99.27%:-nan%)
78139788 + 0 paired in sequencing
39069894 + 0 read1
39069894 + 0 read2
72600556 + 0 properly paired (92.91%:-nan%)
76479896 + 0 with itself and mate mapped
107551 + 0 singletons (0.14%:-nan%)
529216 + 0 with mate mapped to a different chr
49955 + 0 with mate mapped to a different chr (mapQ>=5)
Note that the flagstat command counts alignments, not reads. please
use the read counts table to get accurate counts of reads at each
stage of the pipeline.
Filtering statistics
Mapping quality > q30 (out of total)
48,949,528
0.626
Duplicates (after filtering)
16,091,440
0.681
Mitochondrial reads (out of total)
59,621,557
0.283
Duplicates that are mitochondrial (out of all dups)
30,881,304
0.960
Final reads (after all filters)
15,061,194
0.193
Mapping quality refers to the quality of the read being aligned to that
particular location in the genome. A standard quality score is > 30.
Duplications are often due to PCR duplication rather than two unique reads
mapping to the same location. High duplication is an indication of poor
libraries. Mitochondrial reads are often high in chromatin accessibility
assays because the mitochondrial genome is very open. A high mitochondrial
fraction is an indication of poor libraries. Based on prior experience, a
final read fraction above 0.70 is a good library.
Library complexity statistics
ENCODE library complexity metrics
Metric
Result
NRF
0.900564 - OK
PBC1
0.982775 - OK
PBC2
62.937945 - OK
The non-redundant fraction (NRF) is the fraction of non-redundant mapped reads
in a dataset; it is the ratio between the number of positions in the genome
that uniquely mapped reads map to and the total number of uniquely mappable
reads. The NRF should be > 0.8. The PBC1 is the ratio of genomic locations
with EXACTLY one read pair over the genomic locations with AT LEAST one read
pair. PBC1 is the primary measure, and the PBC1 should be close to 1.
Provisionally 0-0.5 is severe bottlenecking, 0.5-0.8 is moderate bottlenecking,
0.8-0.9 is mild bottlenecking, and 0.9-1.0 is no bottlenecking. The PBC2 is
the ratio of genomic locations with EXACTLY one read pair over the genomic
locations with EXACTLY two read pairs. The PBC2 should be significantly
greater than 1.
Picard EstimateLibraryComplexity
12,559,144
Yield prediction
Preseq performs a yield prediction by subsampling the reads, calculating the
number of distinct reads, and then extrapolating out to see where the
expected number of distinct reads no longer increases. The confidence interval
gives a gauge as to the validity of the yield predictions.
Fragment length statistics
Metric
Result
Fraction of reads in NFR
0.29569181969 out of range [0.4, inf]
NFR / mono-nuc reads
0.695454567137 out of range [2.5, inf]
Presence of NFR peak
OK
Presence of Mono-Nuc peak
OK
Presence of Di-Nuc peak
OK
Open chromatin assays show distinct fragment length enrichments, as the cut
sites are only in open chromatin and not in nucleosomes. As such, peaks
representing different n-nucleosomal (ex mono-nucleosomal, di-nucleosomal)
fragment lengths will arise. Good libraries will show these peaks in a
fragment length distribution and will show specific peak ratios.
Peak statistics
Metric
Result
Naive overlap peaks
162066 - OK
IDR peaks
76312 - OK
Naive overlap peak file statistics
Min size
73.0
25 percentile
228.0
50 percentile (median)
386.0
75 percentile
640.0
Max size
2267.0
Mean
470.962521442
IDR peak file statistics
Min size
73.0
25 percentile
426.0
50 percentile (median)
621.0
75 percentile
864.0
Max size
2267.0
Mean
665.812703114
For a good ATAC-seq experiment in human, you expect to get 100k-200k peaks
for a specific cell type.
Sequence quality metrics
GC bias
Open chromatin assays are known to have significant GC bias. Please take this
into consideration as necessary.
Read count after removing mitochondrial reads (final read count)
16,147,528
Note that all these read counts are determined using 'samtools view' - as such,
these are all reads found in the file, whether one end of a pair or a single
end read. In other words, if your file is paired end, then you should divide
these counts by two. Each step follows the previous step; for example, the
duplicate reads were removed after reads were removed for low mapping quality.
This bar chart also shows the filtering process and where the reads were lost
over the process. Note that each step is sequential - as such, there may
have been more mitochondrial reads which were already filtered because of
high duplication or low mapping quality. Note that all these read counts are
determined using 'samtools view' - as such, these are all reads found in
the file, whether one end of a pair or a single end read. In other words,
if your file is paired end, then you should divide these counts by two.
Alignment statistics
Bowtie alignment log
38415776 reads; of these:
38415776 (100.00%) were paired; of these:
2833839 (7.38%) aligned concordantly 0 times
10478898 (27.28%) aligned concordantly exactly 1 time
25103039 (65.35%) aligned concordantly >1 times
----
2833839 pairs aligned concordantly 0 times; of these:
739480 (26.09%) aligned discordantly 1 time
----
2094359 pairs aligned 0 times concordantly or discordantly; of these:
4188718 mates make up the pairs; of these:
1709286 (40.81%) aligned 0 times
126334 (3.02%) aligned exactly 1 time
2353098 (56.18%) aligned >1 times
97.78% overall alignment rate
Samtools flagstat
204502326 + 0 in total (QC-passed reads + QC-failed reads)
127670774 + 0 secondary
0 + 0 supplementary
0 + 0 duplicates
202793040 + 0 mapped (99.16%:-nan%)
76831552 + 0 paired in sequencing
38415776 + 0 read1
38415776 + 0 read2
71163874 + 0 properly paired (92.62%:-nan%)
75003762 + 0 with itself and mate mapped
118504 + 0 singletons (0.15%:-nan%)
520554 + 0 with mate mapped to a different chr
57048 + 0 with mate mapped to a different chr (mapQ>=5)
Note that the flagstat command counts alignments, not reads. please
use the read counts table to get accurate counts of reads at each
stage of the pipeline.
Filtering statistics
Mapping quality > q30 (out of total)
48,673,489
0.634
Duplicates (after filtering)
15,384,218
0.656
Mitochondrial reads (out of total)
56,646,352
0.279
Duplicates that are mitochondrial (out of all dups)
29,337,840
0.954
Final reads (after all filters)
16,147,528
0.210
Mapping quality refers to the quality of the read being aligned to that
particular location in the genome. A standard quality score is > 30.
Duplications are often due to PCR duplication rather than two unique reads
mapping to the same location. High duplication is an indication of poor
libraries. Mitochondrial reads are often high in chromatin accessibility
assays because the mitochondrial genome is very open. A high mitochondrial
fraction is an indication of poor libraries. Based on prior experience, a
final read fraction above 0.70 is a good library.
Library complexity statistics
ENCODE library complexity metrics
Metric
Result
NRF
0.901536 - OK
PBC1
0.970088 - OK
PBC2
34.663337 - OK
The non-redundant fraction (NRF) is the fraction of non-redundant mapped reads
in a dataset; it is the ratio between the number of positions in the genome
that uniquely mapped reads map to and the total number of uniquely mappable
reads. The NRF should be > 0.8. The PBC1 is the ratio of genomic locations
with EXACTLY one read pair over the genomic locations with AT LEAST one read
pair. PBC1 is the primary measure, and the PBC1 should be close to 1.
Provisionally 0-0.5 is severe bottlenecking, 0.5-0.8 is moderate bottlenecking,
0.8-0.9 is mild bottlenecking, and 0.9-1.0 is no bottlenecking. The PBC2 is
the ratio of genomic locations with EXACTLY one read pair over the genomic
locations with EXACTLY two read pairs. The PBC2 should be significantly
greater than 1.
Picard EstimateLibraryComplexity
13,269,883
Yield prediction
Preseq performs a yield prediction by subsampling the reads, calculating the
number of distinct reads, and then extrapolating out to see where the
expected number of distinct reads no longer increases. The confidence interval
gives a gauge as to the validity of the yield predictions.
Fragment length statistics
Metric
Result
Fraction of reads in NFR
0.347437718642 out of range [0.4, inf]
NFR / mono-nuc reads
0.901382186207 out of range [2.5, inf]
Presence of NFR peak
OK
Presence of Mono-Nuc peak
OK
Presence of Di-Nuc peak
OK
Open chromatin assays show distinct fragment length enrichments, as the cut
sites are only in open chromatin and not in nucleosomes. As such, peaks
representing different n-nucleosomal (ex mono-nucleosomal, di-nucleosomal)
fragment lengths will arise. Good libraries will show these peaks in a
fragment length distribution and will show specific peak ratios.
Peak statistics
Metric
Result
Naive overlap peaks
162066 - OK
IDR peaks
76312 - OK
Naive overlap peak file statistics
Min size
73.0
25 percentile
228.0
50 percentile (median)
386.0
75 percentile
640.0
Max size
2267.0
Mean
470.962521442
IDR peak file statistics
Min size
73.0
25 percentile
426.0
50 percentile (median)
621.0
75 percentile
864.0
Max size
2267.0
Mean
665.812703114
For a good ATAC-seq experiment in human, you expect to get 100k-200k peaks
for a specific cell type.
Sequence quality metrics
GC bias
Open chromatin assays are known to have significant GC bias. Please take this
into consideration as necessary.